Recently, as a part of research associated with pedestrian protection, a pedestrian detecting apparatus is equipped in vehicles and released. The pedestrian detecting apparatus detects a pedestrian that suddenly appears in front of a vehicle, and issues a pedestrian warning to a driver or controls driving of the vehicle, thereby preventing a pedestrian accident.
Proposed conventionally was a pedestrian detecting method that acquires an image from a digital image apparatus, block-converts a search window, and detects a pedestrian by using a full search method based on a Support Vector Machine (SVM) classifier. The pedestrian detecting method removes a number of search windows, and detects a pedestrian by using a secondary classifier having a high degree of precision, thereby reducing power consumption based on a high degree of accuracy and a detection operation. However, in the pedestrian detecting method, the amount of data to be processed for pedestrian detection increases as a resolution of an input image becomes higher, and for this reason, a processing speed is slow.
Another method of the related art acquires a final confidence value that is obtained by combining a confidence value based on an edge-based detection analysis and a confidence value based on a motion-based detection analysis, compares the acquired final confidence value and a threshold value to determine whether a pedestrian is included in an input image, and issues a pedestrian warning to a driver according to the determination result. In such a method, since a motion direction of a whole region of an input image is analyzed due to the motion-based detection analysis, a processing speed is slow as in the pedestrian detecting method using the full search method, and moreover, when there is no movement of a pedestrian, an accuracy of pedestrian detection is low.